citest-mvn: Test for conditional independence in the multivariate normal...

In hojsgaard/gRim: Graphical Interaction Models

Test for conditional independence in the multivariate normal distribution

Description

Test for conditional independence in the multivariate normal distribution.

Usage

ciTest_mvn(x, set = NULL, statistic = "DEV", ...)

Arguments

x	A list with elements cov and n.obs (such as returned from calling cov.wt() on a dataframe. See examples below.)
set	A specification of the test to be made. The tests are of the form u and v are independent condionally on S where u and v are variables and S is a set of variables. See 'details' for details about specification of set.
statistic	The test statistic to be used, valid choices are "DEV" and "F".
...	Additional arguments

Details

set can be 1) a vector or 2) a right-hand sided formula in which variables are separated by '+'. In either case, it is tested if the first two variables in the set are conditionally independent given the remaining variables in set. (Notice an abuse of the '+' operator in the right-hand sided formula: The order of the variables does matter.)

If set is NULL then it is tested whether the first two variables are conditionally independent given the remaining variables.

x must be a list with components cov and n.obs such as returned by calling cov.wt( , method='ML') on a dataframe.

Value

An object of class citest (which is a list).

Author(s)

Søren Højsgaard, [e-mail]

See Also

ciTest, ciTest_table, ciTest_df, ciTest_mvn, chisq.test

Examples

data(carcass)
ciTest(cov.wt(carcass, method='ML'), set=~Fat11 + Meat11 + Fat12)
ciTest_mvn(cov.wt(carcass, method='ML'), set=~Fat11 + Meat11 + Fat12)

hojsgaard/gRim documentation built on Oct. 19, 2024, 10:46 p.m.